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Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge

Title: Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge
Authors: Biggerstaff Matthew; Alper David; Dredze Mark; Fox Spencer; Fung Isaac Chun-Hai; Hickmann Kyle S.; Lewis Bryan; Rosenfeld Roni; Shaman Jeffrey; Tsou Ming-Hsiang; Velardi Paola; Vespignani Alessandro; Finelli Lyn; Chandra Priyadarshini; Kaup Hemchandra; Krishnan Ramesh; Madhavan Satish; Markar Ashirwad; Pashley Bryanne; Paul Michael; Meyers Lauren Ancel; Eggo Rosalind; Henderson Jette; Ramakrishnan Anurekha; Scott James; Singh Bismark; Srinivasan Ravi; Bakach Iurii; Hao Yi; Schaible Braydon J.; Sexton Jessica K.; Del Valle Sara Y.; Deshpande Alina; Fairchild Geoffrey; Generous Nicholas; Priedhorsky Reid; Hickman Kyle S.; Hyman James M.; Brooks Logan; Farrow David; Hyun Sangwon; Tibshirani Ryan J.; Yang Wan; Allen Christopher; Aslam Anoshã; Nagel Anna; Stilo Giovanni; Basagni Stefano; Zhang Qian; Perra Nicola; Chakraborty Prithwish; Butler Patrick; Khadivi Pejman; Ramakrishnan Naren; Chen Jiangzhuo; Barrett Chris; Bisset Keith; Eubank Stephen; Anil Kumar V.S.; Laskowski Kathy; Lum Kristian; Marathe Madhav; Aman Susan; Brownstein John S.; Goldstein Ed; Lipsitch Marc; Mekaru Sumiko R.; Nsoesie Elaine O.; Gesualdo Francesco; Tozzi Alberto E.; Broniatowski David; Karspeck Alicia; Tse Zion Tsz-Ho; Ying Yuchen; Gambhir Manoj; Scarpino Sam
Contributors: Biggerstaff, Matthew; Alper, David; Dredze, Mark; Fox, Spencer; Fung Isaac, Chun-Hai; Hickmann Kyle, S.; Lewis, Bryan; Rosenfeld, Roni; Shaman, Jeffrey; Tsou, Ming-Hsiang; Velardi, Paola; Vespignani, Alessandro; Finelli, Lyn; Chandra, Priyadarshini; Kaup, Hemchandra; Krishnan, Ramesh; Madhavan, Satish; Markar, Ashirwad; Pashley, Bryanne; Paul, Michael; Meyers Lauren, Ancel; Eggo, Rosalind; Henderson, Jette; Ramakrishnan, Anurekha; Scott, Jame; Singh, Bismark; Srinivasan, Ravi; Bakach, Iurii; Hao, Yi; Schaible Braydon, J.; Sexton Jessica, K.; Del Valle Sara, Y.; Deshpande, Alina; Fairchild, Geoffrey; Generous, Nichola; Priedhorsky, Reid; Hickman Kyle, S.; Hyman James, M.; Brooks, Logan; Farrow, David; Hyun, Sangwon; Tibshirani Ryan, J.; Yang, Wan; Allen, Christopher; Aslam, Anoshã; Nagel, Anna; Stilo, Giovanni; Basagni, Stefano; Zhang, Qian; Perra, Nicola; Chakraborty, Prithwish; Butler, Patrick; Khadivi, Pejman; Ramakrishnan, Naren; Chen, Jiangzhuo; Barrett, Chri; Bisset, Keith; Eubank, Stephen; Anil Kumar, V. S.; Laskowski, Kathy; Lum, Kristian; Marathe, Madhav; Aman, Susan; Brownstein John, S.; Goldstein, Ed; Lipsitch, Marc; Mekaru Sumiko, R.; Nsoesie Elaine, O.; Gesualdo, Francesco; Tozzi Alberto, E.; Broniatowski, David; Karspeck, Alicia; Tse Zion, Tsz-Ho; Ying, Yuchen; Gambhir, Manoj; Scarpino, Sam
Publication Year: 2016
Collection: LUISS Guido Carli: IRIS (Libera Università Internazionale degli Studi Sociali, Roma)
Subject Terms: Influenza; Forecasting; Modeling; Prediction; Human; Model; Statistical; Public Health Surveillance; United State; Centers for Disease Control and Prevention (U.S.); Biological; Season; Infectious Diseases
Description: Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013–14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013–2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013–March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts.
Document Type: article in journal/newspaper
Language: English
Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:000380995100001; volume:16; issue:1; firstpage:1; lastpage:10; numberofpages:10; journal:BMC INFECTIOUS DISEASES; https://hdl.handle.net/11385/253779
DOI: 10.1186/s12879-016-1669-x
Availability: https://hdl.handle.net/11385/253779; https://doi.org/10.1186/s12879-016-1669-x; https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-016-1669-x
Rights: info:eu-repo/semantics/openAccess ; license:Creative commons ; license uri:http://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.91EF5A32
Database: BASE